网状高效排序双向链表

这是一个表头用网状的排序双向链表结构托管类，原本开发的原因是游戏服务器根据玩家战斗力排序的容器更新 & 查找效率不理想，希望有个新的方法替代，因为战斗力变化频率比较高，多个用户又可能是相同的战斗力，所以做了这个类似跳跃表的结构对数据分段

enum EN_GRIDDING_SORT{en_grd_sort_up,en_grd_sort_down,};template<class _Ty>struct gridding_node{_Ty _value;struct gridding_node* _prev;struct gridding_node* _next;struct gridding_node* _upper;struct gridding_node* _downer;gridding_node(): _prev(NULL), _next(NULL), _upper(NULL), _downer(NULL){}bool is_header(){return _upper != NULL || _downer != NULL;}};////// 网状双向链表托管（类似跳跃表）/// H1 = N11 = N12 = N13..../// ||/// H2 = N21 = N22..../// ||/// H3 = N31 = N32..../// [11/2/2016] create by jianglei.kinly///template<class _Ty, class _Ty_rule, EN_GRIDDING_SORT en>class gridding_list{typedef _Ty_rule(*FUNC_rule)(const _Ty& value);typedef bool(*FUNC_search_filter)(const _Ty& value);private:gridding_node<_Ty>* m_pHeader;FUNC_rule m_pFuncRule;private:static gridding_node<_Ty>* create_header(const _Ty & value){gridding_node<_Ty>* pNewer = new gridding_node<_Ty>();pNewer->_value = value;gridding_node<_Ty>* pNewerNode = create_node(value);pNewer->_next = pNewerNode;pNewerNode->_prev = pNewer;return pNewer;}static gridding_node<_Ty>* create_node(const _Ty & value){gridding_node<_Ty>* pNewer = new gridding_node<_Ty>();pNewer->_value = value;return pNewer;}private:gridding_list(){}gridding_node<_Ty>* row_head(gridding_node<_Ty>* node){gridding_node<_Ty>* head = node;if (node){while (head->_prev)head = head->_prev;}return head;}gridding_node<_Ty>* row_end(gridding_node<_Ty>* node){gridding_node<_Ty>* end = node;if (node){while (end->_next)end = end->_next;}return end;}public:gridding_list(FUNC_rule fnRule): m_pHeader(NULL), m_pFuncRule(fnRule){}bool insert(const _Ty & value){if (m_pFuncRule == NULL)return false;if (m_pHeader == NULL){m_pHeader = create_header(value);return true;}gridding_node<_Ty>* pRow = NULL;if (m_pFuncRule(m_pHeader->_value) == m_pFuncRule(value))pRow = m_pHeader;else if ((m_pFuncRule(m_pHeader->_value) > m_pFuncRule(value) && en == en_grd_sort_up) || (m_pFuncRule(m_pHeader->_value) < m_pFuncRule(value) && en == en_grd_sort_down)){pRow = create_header(value);pRow->_downer = m_pHeader;m_pHeader->_upper = pRow;m_pHeader = pRow;return true;}else{gridding_node<_Ty>* pCurr = m_pHeader;while (pCurr->_downer){if (m_pFuncRule(pCurr->_downer->_value) == m_pFuncRule(value)){pRow = pCurr->_downer;break;}else if ((m_pFuncRule(pCurr->_downer->_value) > m_pFuncRule(value) && en == en_grd_sort_up) || (m_pFuncRule(pCurr->_downer->_value) < m_pFuncRule(value) && en == en_grd_sort_down)){pRow = create_header(value);pRow->_downer = pCurr->_downer;pRow->_upper = pCurr;pCurr->_downer->_upper = pRow;pCurr->_downer = pRow;return true;}elsepCurr = pCurr->_downer;}if (pRow == NULL){if (pCurr){pRow = create_header(value);pRow->_upper = pCurr;pCurr->_downer = pRow;return true;}}}if (pRow == NULL || pRow->_next == NULL)return false;gridding_node<_Ty>* pCurrNode = pRow->_next;while (pCurrNode){if (pCurrNode->_value == value){pCurrNode->_value.merge(value);return true;}else if ((pCurrNode->_value > value && en == en_grd_sort_up) || (pCurrNode->_value < value && en == en_grd_sort_down)){gridding_node<_Ty>* pCol = create_node(value);pCol->_next = pCurrNode;pCol->_prev = pCurrNode->_prev;pCurrNode->_prev->_next = pCol;pCurrNode->_prev = pCol;return true;}else{if (pCurrNode->_next == NULL){gridding_node<_Ty>* pCol = create_node(value);pCurrNode->_next = pCol;pCol->_prev = pCurrNode;return true;}elsepCurrNode = pCurrNode->_next;}}return false;}_Ty * search(const _Ty& value){if (m_pFuncRule == NULL)return NULL;gridding_node<_Ty>* pCurr = m_pHeader;while (pCurr){if (pCurr){if (m_pFuncRule(pCurr->_value) == m_pFuncRule(value))break;}pCurr = pCurr->_downer;}if (pCurr){pCurr = pCurr->_next;while (pCurr){if (pCurr->_value == value)return &(pCurr->_value);pCurr = pCurr->_next;}}return NULL;}// 按半径搜索bool search_radius(const _Ty& center, uint32_t dwRadius, std::vector<_Ty>& vecRes){if (m_pFuncRule == NULL)return false;gridding_node<_Ty>* pCurr = m_pHeader;while (pCurr){if (m_pFuncRule(pCurr->_value) == m_pFuncRule(center))break;pCurr = pCurr->_downer;}if (pCurr){pCurr = pCurr->_next;while (pCurr){if (pCurr->_value == center)break;pCurr = pCurr->_next;}}if (pCurr == NULL)return false;vecRes.push_back(pCurr->_value);gridding_node<_Ty>* pCenter = pCurr;// 向前for (uint32_t i = 1; i < dwRadius; ++i){if (pCurr->_prev && pCurr->_prev->is_header() == false){pCurr = pCurr->_prev;vecRes.push_back(pCurr->_value);}else{// upper rowgridding_node<_Ty>* pRowHead = row_head(pCurr);if (pRowHead && pRowHead->_upper){// 取尾部pCurr = row_end(pRowHead->_upper);vecRes.push_back(pCurr->_value);}elsebreak;}}pCurr = pCenter;// 向后for (uint32_t i = 1; i < dwRadius; ++i){if (pCurr->_next){pCurr = pCurr->_next;vecRes.push_back(pCurr->_value);}else{// downer rowgridding_node<_Ty>* pRowHead = row_head(pCurr);if (pRowHead && pRowHead->_downer){pCurr = pRowHead->_downer->_next;vecRes.push_back(pCurr->_value);}elsebreak;}}return true;}// 按照自定规则搜索bool search_filter(const _Ty& center, FUNC_search_filter fnFilter, std::vector<_Ty>& vecRes){if (m_pFuncRule == NULL)return false;gridding_node<_Ty>* pRow = m_pHeader;while (pRow){if (m_pFuncRule(pRow->_value) == m_pFuncRule(center))break;pRow = pRow->_downer;}// 这里只找行，列就不找了if (pRow == NULL)return false;gridding_node<_Ty>* pCurr = pRow->_next;if (pCurr == NULL)return false;if(fnFilter == NULL || fnFilter(pCurr->_value))vecRes.push_back(pCurr->_value);// 向前while(true){if (pCurr->_prev && pCurr->_prev->is_header() == false){pCurr = pCurr->_prev;if (fnFilter == NULL || fnFilter(pCurr->_value))vecRes.push_back(pCurr->_value);elsebreak; // 因为是排序表，fnFilter认为是已知该规则的筛选，如果出现不符的，前面的都不处理了}else{// upper rowgridding_node<_Ty>* pRowHead = row_head(pCurr);if (pRowHead && pRowHead->_upper){pCurr = row_end(pRowHead->_upper);if (fnFilter == NULL || fnFilter(pCurr->_value))vecRes.push_back(pCurr->_value);elsebreak; // 因为是排序表，fnFilter认为是已知该规则的筛选，如果出现不符的，前面的都不处理了}elsebreak;}}pCurr = pRow->_next;// 向后while (true){if (pCurr->_next){pCurr = pCurr->_next;if (fnFilter == NULL || fnFilter(pCurr->_value))vecRes.push_back(pCurr->_value);elsebreak; // 因为是排序表，fnFilter认为是已知该规则的筛选，如果出现不符的，后面的都不处理了}else{// downer rowgridding_node<_Ty>* pRowHead = row_head(pCurr);if (pRowHead && pRowHead->_downer){pCurr = pRowHead->_downer->_next;if (fnFilter == NULL || fnFilter(pCurr->_value))vecRes.push_back(pCurr->_value);elsebreak; // 因为是排序表，fnFilter认为是已知该规则的筛选，如果出现不符的，后面的都不处理了}elsebreak;}}return true;}uint32_t rank(const _Ty& value){uint32_t dwRank = 0;if (m_pFuncRule == NULL)return dwRank;gridding_node<_Ty>* pCurr = m_pHeader;while (pCurr){pCurr = pCurr->_next;while (pCurr){dwRank += pCurr->_value.size();if (pCurr->_value == center)break;pCurr = pCurr->_next;}if (m_pFuncRule(pCurr->_value) == m_pFuncRule(center))break;pCurr = pCurr->_downer;}return dwRank;}};// 测试用例 [11/2/2016 jianglei.kinly]#include <vector>struct grid_test_data{uint32_t _key;std::vector<uint32_t> _value;uint32_t _count;grid_test_data(): _key(0), _count(1){}grid_test_data(uint32_t a){_key = a;_count = 1;}grid_test_data& operator = (const grid_test_data& td){_key = td._key;_value.clear();_value = td._value;return *this;}bool operator == (const grid_test_data& td){return _key == td._key;}bool operator > (const grid_test_data& td){return _key > td._key;}bool operator < (const grid_test_data& td){return _key < td._key;}friend std::ostream& operator << (std::ostream& out, const grid_test_data& td){out << td._key << "(" << td._count << ")";return out;}void merge(const grid_test_data& td){_value.insert(_value.end(), td._value.begin(), td._value.end());_count += td._count;}uint32_t key(){return _key;}uint32_t key() const{return _key;}uint32_t count(){return _count;}uint32_t count() const{return _count;}std::vector<uint32_t>& value(){return _value;}};

template<class _T>  uint32_t rule_calc_row(const _T& value)  {      return value.key() / 100;  }    random_help rh;  gridding_list<grid_test_data, uint32_t, en_grd_sort_up> g_list(rule_calc_row<grid_test_data>);  for (int i = 0; i < 1024 * 1024; ++i)  {      grid_test_data td01(rh(1, 10240));      if (g_list.insert(td01) == false)      {          std::cout << __FUNCTION__ << "," << __LINE__ << td01.key() << std::endl;          break;      }  }  

上面是测试用的规则、测试代码，random_help是之前写的一个随机函数类
centos开发环境
1024 * 1024 分散量级 10240的数据实际插入耗时是4.6s
单条查找耗时 < 1ms
满足需求